We appreciate the attention that readers have given our efforts to
help clinicians learn key concepts in practicing evidence-based medicine.
Professor Tevaarwerk has kindly described our presentation of spectrum
bias1 as ‘delightful in its simplicity’, a comment that is in line with
our intention. We completely agree with Professor Tevaarwerk and we
believe that widespread adoption of likelihood ratios to describe
diagnostic test results is essential for the practice of evidence-based
laboratory medicine and diagnostics.2 Professor Tevaarwerk’s sharp eye
has identified a potentially misleading aspect of how Figure 3 was drawn
in our article. Namely, the likelihood ratios corresponding to test
values appear to decrease with increasing values in one small portion of
the right hand side of the graphic. Had we used actual probability
density curves, rather than simply made up the figures for purposes of
qualitative demonstration, we would have avoided this visual artifact.3
The figure conveys, nevertheless, the fundamental concept of the
relationship between probability distributions in target positive and
target negative populations, and the associated likelihood ratios. We have
provided a number of examples of contexts in which test characteristics
may differ in subpopulations, including BNP in patients with and without
underlying lung disease. Mr. Bhaskar provides other examples of the same
phenomenon. He frames the issue in terms of confounders; we find it
simpler to think of different subpopulations. Whatever the formulation,
Mr. Bhaskar is correct that pooling results from subpopulations in which
tests perform very differently may be misleading.

We appreciate Professor Hall’s detailed review of our manuscript.
The teachers’ version of our article makes the point more clearly.4 We
regret that it became a bit “muddled” in the learners’ version. We
intended it to be clear to the readers that disease spectrum will affect
diagnostic test characteristics (i.e., likelihood ratios) while prevalence
will not.

4. Montori VM, Wyer P, Newman TB, Keitz S, Guyatt G, for the Evidence
Based Medicine Teaching Tips Working Group. Tips For Teachers Of Evidence-
Based Medicine: 5. The Effect Of Spectrum Of Disease On The Performance Of
Diagnostic Tests. CMAJ. 2005;173:Online 1-Online 7 Available at
http://www.cmaj.ca/cgi/data/173/4/385/DC1/1 (Accessed on December 30,
2005).

Conflict of Interest:

This instalment of TIPS was informative and delightful in its
simplicity.
However, the graphic representation of the likelihood ratio (LR) formula
in
figure 3 is incorrect. The two likelihoods sensitivity (Sens) and
specificity
(Spec), are plotted as relative frequencies instead of cumulative ones,
resulting in erroneous LR values. This is clearly demonstrated by the
decrease
in LR values as Sens approaches zero, eve...

This instalment of TIPS was informative and delightful in its
simplicity.
However, the graphic representation of the likelihood ratio (LR) formula
in
figure 3 is incorrect. The two likelihoods sensitivity (Sens) and
specificity
(Spec), are plotted as relative frequencies instead of cumulative ones,
resulting in erroneous LR values. This is clearly demonstrated by the
decrease
in LR values as Sens approaches zero, eventhough the analytical values are
increasing.

In clinical practice Sens and Spec never reach zero, as there is
always the
probability of a 'transcription error'. (1) Assuming it to be at least 1%
the
range of LR values is effectively slightly more tha 0 and slightly less
than 100.
This familiar range makes it an ideal candidate to express the diagnostic
power of all clinical features and diagnostic tests on a common universal
reporting scale.

The adoption of Universal Reporting Units (URU) would do away with
the need
for the myriad of analytical reporting scales and reference ranges, while
making diagnostic power values not only independent of prevalence but
universally portable. Its ease of use in revising diagnostic
probabilities,
especially when expressed as odds to the sum of 100 where they are
synonymous with % values, (2) and use as a denominator to compare 'value
for cost', offers the possibility of the more frugal use of increasingly
scarce
resources. (1)

Montori and collegues in their review have stressed the importance of
“disease spectrum” in the evaluation of diagnostic tests(1).The role
played by known confounders (factors which produce biased estimate) in the
interpretation of diagnostic test demands attention(2). Glomerular
filtration rate[GFR] is an important confounder in the context of brain
natriuretic peptide[BNP] levels. BNP levels are inve...

Montori and collegues in their review have stressed the importance of
“disease spectrum” in the evaluation of diagnostic tests(1).The role
played by known confounders (factors which produce biased estimate) in the
interpretation of diagnostic test demands attention(2). Glomerular
filtration rate[GFR] is an important confounder in the context of brain
natriuretic peptide[BNP] levels. BNP levels are inversely proportional to
GFR and the ideal cut-off values for different range of GFR is yet to be
identified(3). Additional confounders exist and should be considered
before interpreting the test(4). Similarly troponin levels should be
cautiously interpreted in the context of other potential confounders like
heart failure, cardiomyopathy and sepsis (5).

Papers describing clinical utility of diagnostic test often fail to
address the data on these confounders leading to improper patient
selection and misinterpretation of the test.

References:

1.Victor M.Montori,Peter Wyer,Thomas B.Newman,Sheri Keitz,Gordon
Guyatt,et al. Tips for learners of evidence based medicine:5.The effect of
spectrum of disease on the performance of diagnostic tests.CMAJ
2005;173:385-390

The first "bullet" states that "Disease prevalence has no direct
effect on test characteristics", a dichotomous "does/does not" assertion.
The second states that "Spectrum of disease and disease prevalence have
different effects on diagnostic test characteristics", a comparative
statement i...

The first "bullet" states that "Disease prevalence has no direct
effect on test characteristics", a dichotomous "does/does not" assertion.
The second states that "Spectrum of disease and disease prevalence have
different effects on diagnostic test characteristics", a comparative
statement implying that both have effects.

This leaves the reader to resolve whether:
(a) the comparison implied in the second bullet is between something and
nothing
(b) disease prevalence has INDIRECT effects on test characteristics (which
differ from those of disease spectrum, whether direct or indirect), which
must be relevant otherwise why make the comparison, or...
(c) the authors are muddled.